DBMS > Atos Standard Common Repository vs. Hypertable vs. IBM Db2 Event Store vs. SiriDB vs. TimescaleDB

System Properties Comparison Atos Standard Common Repository vs. Hypertable vs. IBM Db2 Event Store vs. SiriDB vs. TimescaleDB

Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Hypertable  Xexclude from comparison	IBM Db2 Event Store  Xexclude from comparison	SiriDB  Xexclude from comparison	TimescaleDB  Xexclude from comparison
	This system has been discontinued and will be removed from the DB-Engines ranking.	Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
Description	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	An open source BigTable implementation based on distributed file systems such as Hadoop	Distributed Event Store optimized for Internet of Things use cases	Open Source Time Series DBMS	A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database model	Document store Key-value store	Wide column store	Event Store Time Series DBMS	Time Series DBMS	Time Series DBMS
Secondary database models					Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart			Score 0.27 Rank #309   Overall #2   Event Stores #28   Time Series DBMS	Score 0.07 Rank #378   Overall #42   Time Series DBMS	Score 4.46 Rank #71   Overall #5   Time Series DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository		www.ibm.com/­products/­db2-event-store	siridb.com	www.timescale.com
Technical documentation			www.ibm.com/­docs/­en/­db2-event-store	docs.siridb.com	docs.timescale.com
Developer	Atos Convergence Creators	Hypertable Inc.	IBM	Cesbit	Timescale
Initial release	2016	2009	2017	2017	2017
Current release	1703	0.9.8.11, March 2016	2.0		2.15.0, May 2024
License Commercial or Open Source	commercial	Open Source GNU version 3. Commercial license available	commercial free developer edition available	Open Source MIT License	Open Source Apache 2.0
Cloud-based only Only available as a cloud service	no	no	no	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	C++	C and C++	C	C
Server operating systems	Linux	Linux OS X Windows an inofficial Windows port is available	Linux Linux, macOS, Windows for the developer addition	Linux	Linux OS X Windows
Data scheme	Schema and schema-less with LDAP views	schema-free	yes	yes	yes
Typing predefined data types such as float or date	optional	no	yes	yes Numeric data	numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.	yes		no	no	yes
Secondary indexes	yes	restricted only exact value or prefix value scans	no	yes	yes
SQL Support of SQL	no	no	yes through the embedded Spark runtime	no	yes full PostgreSQL SQL syntax
APIs and other access methods	LDAP	C++ API Thrift	ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API	HTTP API	ADO.NET JDBC native C library ODBC streaming API for large objects
Supported programming languages	All languages with LDAP bindings	C++ Java Perl PHP Python Ruby	C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic	C C++ Go Java JavaScript (Node.js) PHP Python R	.Net C C++ Delphi Java JDBC JavaScript Perl PHP Python R Ruby Scheme Tcl
Server-side scripts Stored procedures	no	no	yes	no	user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggers	yes	no	no	no	yes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding	Sharding	Sharding	yes, across time and space (hash partitioning) attributes
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor on file system level	Active-active shard replication	yes	Source-replica replication with hot standby and reads on replicas
MapReduce Offers an API for user-defined Map/Reduce methods		yes	no	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Eventual Consistency		Immediate Consistency
Foreign keys Referential integrity	no	no	no	no	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no	no	no	ACID
Concurrency Support for concurrent manipulation of data	yes	yes	No - written data is immutable	yes	yes
Durability Support for making data persistent	yes	yes	Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		yes	yes	no
User concepts Access control	LDAP bind authentication	no	fine grained access rights according to SQL-standard	simple rights management via user accounts	fine grained access rights according to SQL-standard
More information provided by the system vendor We invite representatives of system vendors to contact us for updating and extending the system information, and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.
Related products and services We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
More resources
	Atos Standard Common Repository	Hypertable	IBM Db2 Event Store	SiriDB	TimescaleDB
Recent citations in the news			Advancements in streaming data storage, real-time analysis and machine learning 25 July 2019, IBM How IBM Is Turning Db2 into an 'AI Database' 3 June 2019, Datanami Best cloud databases of 2022 4 October 2022, ITPro provided by Google News		TimescaleDB Is a Vector Database Now, Too 25 September 2023, Datanami Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers 4 April 2024, PR Newswire Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL 18 March 2019, Microsoft Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data 22 February 2022, businesswire.com TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out 22 August 2019, Packt Hub provided by Google News

Share this page